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Microsoft DP-100 Exam Dumps
Designing and Implementing a Data Science Solution on Azure
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Microsoft DP-100 Sample Questions
Question # 1You need to implement a scaling strategy for the local penalty detection data.Which normalization type should you use?
A. Streaming
B. Weight
C. Batch
D. Cosine
Question # 2
You need to resolve the local machine learning pipeline performance issue. What should you do?
A. Increase Graphic Processing Units (GPUs).
B. Increase the learning rate.
C. Increase the training iterations,
D. Increase Central Processing Units (CPUs).
Question # 3
You need to implement a model development strategy to determine a user’s tendency to respond to an ad.Which technique should you use?
A. Use a Relative Expression Split module to partition the data based on centroid distance.
B. Use a Relative Expression Split module to partition the data based on distance travelled to the event.
C. Use a Split Rows module to partition the data based on distance travelled to the event.
D. Use a Split Rows module to partition the data based on centroid distance.
Question # 4
You need to select an environment that will meet the business and data requirements.Which environment should you use?
A. Azure HDInsight with Spark MLlib
B. Azure Cognitive Services
C. Azure Machine Learning Studio
D. Microsoft Machine Learning Server
Question # 5
You need to implement a feature engineering strategy for the crowd sentiment local models.What should you do?
A. Apply an analysis of variance (ANOVA).
B. Apply a Pearson correlation coefficient.
C. Apply a Spearman correlation coefficient.
D. Apply a linear discriminant analysis.
Question # 6
You need to select a feature extraction method.Which method should you use?
A. Spearman correlation
B. Mutual information
C. Mann-Whitney test
D. Pearson’s correlation
Question # 7
You need to select a feature extraction method.Which method should you use?
A. Mutual information
B. Mood’s median test
C. Kendall correlation
D. Permutation Feature Importance
Question # 8
Your team is building a data engineering and data science development environment.The environment must support the following requirements:support Python and Scalacompose data storage, movement, and processing services into automated datapipelinesthe same tool should be used for the orchestration of both data engineering anddata sciencesupport workload isolation and interactive workloadsenable scaling across a cluster of machinesYou need to create the environment.What should you do?
A. Build the environment in Apache Hive for HDInsight and use Azure Data Factory fororchestration.
B. Build the environment in Azure Databricks and use Azure Data Factory for orchestration.
C. Build the environment in Apache Spark for HDInsight and use Azure ContainerInstances for orchestration.
D. Build the environment in Azure Databricks and use Azure Container Instances fororchestration.
Question # 9
You create a classification model with a dataset that contains 100 samples with Class Aand 10,000 samples with Class BThe variation of Class B is very high.You need to resolve imbalances.Which method should you use?
A. Partition and Sample
B. Cluster Centroids
C. Tomek links
D. Synthetic Minority Oversampling Technique (SMOTE)
Question # 10
You are building a binary classification model by using a supplied training set.The training set is imbalanced between two classes.You need to resolve the data imbalance.What are three possible ways to achieve this goal? Each correct answer presents acomplete solution NOTE: Each correct selection is worth one point.
A. Penalize the classification
B. Resample the data set using under sampling or oversampling
C. Generate synthetic samples in the minority class.
D. Use accuracy as the evaluation metric of the model.
E. Normalize the training feature set.
Question # 11
You need to select a pre built development environment for a series of data scienceexperiments. You must use the R language for the experiments.Which three environments can you use? Each correct answer presents a completesolution. NOTE: Each correct selection is worth one point.
A. MI.NET Library on a local environment
B. Azure Machine Learning Studio
C. Data Science Virtual Machine (OSVM)
D. Azure Data bricks
E. Azure Cognitive Services
Question # 12
Note: This question is part of a series of questions that present the same scenario. Eachquestion in the series contains a unique solution that might meet the stated goals. Somequestion sets might have more than one correct solution, while others might not have acorrect solution.After you answer a question in this section, you will NOT be able to return to it. As a result,these questions will not appear in the review screen.You are analyzing a numerical dataset which contains missing values in several columns.You must clean the missing values using an appropriate operation without affecting thedimensionality of the feature set.You need to analyze a full dataset to include all values.Solution: Calculate the column median value and use the median value as the replacementfor any missing value in the column.Does the solution meet the goal?
A. Yes
B. No
Question # 13
You are solving a classification task.The dataset is imbalanced.You need to select an Azure Machine Learning Studio module to improve the classification accuracy.Which module should you use?
A. Fisher Linear Discriminant Analysis.
B. Filter Based Feature Selection
C. Synthetic Minority Oversampling Technique (SMOTE)
D. Permutation Feature Importance
Question # 14
Note: This question is part of a series of questions that present the same scenario.Each question in the series contains a unique solution that might meet the statedgoals. Some question sets might have more than one correct solution, while othersmight not have a correct solution.After you answer a question in this section, you will NOT be able to return to it. As a result, thesequestions will not appear in the review screen.You are creating a model to predict the price of a student’s artwork depending on thefollowing variables: the student’s length of education, degree type, and art form.You start by creating a linear regression model.You need to evaluate the linear regression model.Solution: Use the following metrics: Accuracy, Precision, Recall, F1 score and AUC.Does the solution meet the goal?
A. Yes
B. No
Question # 15
Note: This question is part of a series of questions that present the same scenario. Eachquestion in the series contains a unique solution that might meet the stated goals. Somequestion sets might have more than one correct solution, while others might not have a correct solution.After you answer a question in this section, you will NOT be able to return to it. As a result,these questions will not appear in the review screen.You are analyzing a numerical dataset which contains missing values in several columns.You must clean the missing values using an appropriate operation without affecting thedimensionality of the feature set.You need to analyze a full dataset to include all values.Solution: Remove the entire column that contains the missing data point.Does the solution meet the goal?
A. Yes
B. No
Question # 16
You are a data scientist building a deep convolutional neural network (CNN) for image classification.The CNN model you built shows signs of overfitting.You need to reduce overfitting and converge the model to an optimal fit.Which two actions should you perform? Each correct answer presents a complete solution.NOTE: Each correct selection is worth one point.
A. Reduce the amount of training data.
B. Add an additional dense layer with 64 input units
C. Add L1/L2 regularization.
D. Use training data augmentation
E. Add an additional dense layer with 512 input units.
Question # 17
You are with a time series dataset in Azure Machine Learning Studio.You need to split your dataset into training and testing subsets by using the Split Data module.Which splitting mode should you use?
A. Regular Expression Split
B. Split Rows with the Randomized split parameter set to true
C. Relative Expression Split
D. Recommender Split
Question # 18
You are evaluating a completed binary classification machine.You need to use the precision as the evaluation metric.Which visualization should you use?
A. scatter plot
B. coefficient of determination
C. Receiver Operating Characteristic CROC) curve
D. Gradient descent
Question # 19
Note: This question is part of a series of questions that present the same scenario. Eachquestion in the series contains a unique solution that might meet the stated goals. Somequestion sets might have more than one correct solution, while others might not have acorrect solution.After you answer a question in this section, you will NOT be able to return to it. As a result,these questions will not appear in the review screen.You are analyzing a numerical dataset which contains missing values in several columns.You must clean the missing values using an appropriate operation without affecting thedimensionality of the feature set.You need to analyze a full dataset to include all values.Solution: Replace each missing value using the Multiple Imputation by Chained Equations(MICE) method.Does the solution meet the goal?
A. Yes
B. NO
Question # 20
You arc creating a new experiment in Azure Machine Learning Studio. You have a smalldataset that has missing values in many columns. The data does not require theapplication of predictors for each column. You plan to use the Clean Missing Data moduleto handle the missing data.You need to select a data cleaning method.Which method should you use?
A. Synthetic Minority
B. Replace using Probabilistic PAC
C. Replace using MICE
D. Normalization